{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nltk.corpus import stopwords\n",
    "from sklearn.metrics.pairwise import linear_kernel\n",
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "from sklearn.decomposition import LatentDirichletAllocation\n",
    "import random\n",
    "import re, nltk, spacy, gensim\n",
    "import pyLDAvis\n",
    "import pyLDAvis.sklearn\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "pd.set_option('display.max_columns', 50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('data/Seattle_Hotels_dirty.csv', encoding=\"latin-1\")\n",
    "df.set_index('name', inplace = True)\n",
    "tf = TfidfVectorizer(analyzer='word', ngram_range=(1, 3), min_df=0, stop_words='english')\n",
    "tfidf_matrix = tf.fit_transform(df['desc'])\n",
    "cosine_similarities = linear_kernel(tfidf_matrix, tfidf_matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "indices = pd.Series(df.index)\n",
    "def recommendations(name, cosine_similarities = cosine_similarities):\n",
    "    \n",
    "    recommended_hotels = []\n",
    "    \n",
    "    # gettin the index of the hotel that matches the name\n",
    "    idx = indices[indices == name].index[0]\n",
    "\n",
    "    # creating a Series with the similarity scores in descending order\n",
    "    score_series = pd.Series(cosine_similarities[idx]).sort_values(ascending = False)\n",
    "\n",
    "    # getting the indexes of the 5 most similar hotels except itself\n",
    "    top_10_indexes = list(score_series.iloc[1:6].index)\n",
    "    \n",
    "    # populating the list with the names of the top 5 matching hotels\n",
    "    for i in top_10_indexes:\n",
    "        recommended_hotels.append(list(df.index)[i])\n",
    "        \n",
    "    return recommended_hotels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Hilton Seattle',\n",
       " \"Mildred's Bed and Breakfast\",\n",
       " 'Seattle Airport Marriott',\n",
       " 'Days Inn by Wyndham Seattle North of Downtown',\n",
       " 'Holiday Inn Express & Suites North Seattle - Shoreline']"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recommendations('Hilton Garden Inn Seattle Downtown')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Located on the southern tip of Lake Union, the Hilton Garden Inn Seattle Downtown hotel is perfectly located for business and leisure. Non-Smoking\\nHotel is 100% non-smoking, including e-cigarettes, in all guest rooms and public areas. A fee of up to $250 USD will be assessed for smoking in a non-smoking room. Please ask the Front Desk for locations of designated outdoor smoking areas. Check-in: 4:00 pm. Check-out: 12:00 pm. Cancellation policies may vary depending on the rate or dates of your reservation. Please refer to your reservation confirmation to verify your cancellation policy.\\n'"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc['Hilton Garden Inn Seattle Downtown'].desc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'A rare find in the heart of Seattle. 100% non-smoking. Check-in: 4:00 pm. Check-out: 12:00 pm. Cancellation policies may vary depending on the rate or dates of your reservation.'"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[\"Mildred's Bed and Breakfast\"].desc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'We streamline your travel routine. Explore the local area, brimming with alluring attractions. Reserve one of our 14 versatile event spaces for your next business meeting or wedding reception. We also feature an outdoor atrium, which provides a gorgeous backdrop for intimate gatherings. Check-in: 4:00 PM, Check-out: 12:00 PM. We are committed to providing our guests and associates with a smoke-free environment, and are proud to boast one of the most comprehensive smoke-free hotel policies in the industry. Although smoking is not permitted within hotel buildings themselves, guests who smoke are permitted to do so outside in designated areas.'"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[\"Seattle Airport Marriott\"].desc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We have  1208 sentences in total\n"
     ]
    }
   ],
   "source": [
    "df = pd.concat([pd.Series(str(row['name']), str(row['desc']).split('. '))              \n",
    "                    for _, row in df.iterrows()]).reset_index()\n",
    "df.columns = ['sentence', 'name']\n",
    "df['sentence'] = df['sentence'].map(lambda x: re.sub(r'\\W+', ' ', x))\n",
    "print('We have ', len(df), 'sentences in total')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sentence</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Located on the southern tip of Lake Union the ...</td>\n",
       "      <td>Hilton Garden Inn Seattle Downtown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Non Smoking Hotel is 100 non smoking including...</td>\n",
       "      <td>Hilton Garden Inn Seattle Downtown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>A fee of up to 250 USD will be assessed for sm...</td>\n",
       "      <td>Hilton Garden Inn Seattle Downtown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Please ask the Front Desk for locations of des...</td>\n",
       "      <td>Hilton Garden Inn Seattle Downtown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Check in 4 00 pm</td>\n",
       "      <td>Hilton Garden Inn Seattle Downtown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Check out 12 00 pm</td>\n",
       "      <td>Hilton Garden Inn Seattle Downtown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Cancellation policies may vary depending on th...</td>\n",
       "      <td>Hilton Garden Inn Seattle Downtown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Please refer to your reservation confirmation ...</td>\n",
       "      <td>Hilton Garden Inn Seattle Downtown</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            sentence  \\\n",
       "0  Located on the southern tip of Lake Union the ...   \n",
       "1  Non Smoking Hotel is 100 non smoking including...   \n",
       "2  A fee of up to 250 USD will be assessed for sm...   \n",
       "3  Please ask the Front Desk for locations of des...   \n",
       "4                                   Check in 4 00 pm   \n",
       "5                                 Check out 12 00 pm   \n",
       "6  Cancellation policies may vary depending on th...   \n",
       "7  Please refer to your reservation confirmation ...   \n",
       "\n",
       "                                 name  \n",
       "0  Hilton Garden Inn Seattle Downtown  \n",
       "1  Hilton Garden Inn Seattle Downtown  \n",
       "2  Hilton Garden Inn Seattle Downtown  \n",
       "3  Hilton Garden Inn Seattle Downtown  \n",
       "4  Hilton Garden Inn Seattle Downtown  \n",
       "5  Hilton Garden Inn Seattle Downtown  \n",
       "6  Hilton Garden Inn Seattle Downtown  \n",
       "7  Hilton Garden Inn Seattle Downtown  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df['name'] == 'Hilton Garden Inn Seattle Downtown']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Located on the southern tip of Lake Union the Hilton Garden Inn Seattle Downtown hotel is perfectly located for business and leisure\n",
      "\n",
      "Non Smoking Hotel is 100 non smoking including e cigarettes in all guest rooms and public areas\n",
      "\n",
      "A fee of up to 250 USD will be assessed for smoking in a non smoking room\n",
      "\n",
      "Please ask the Front Desk for locations of designated outdoor smoking areas\n",
      "\n",
      "Check in 4 00 pm\n",
      "\n",
      "Check out 12 00 pm\n",
      "\n",
      "Cancellation policies may vary depending on the rate or dates of your reservation\n",
      "\n",
      "Please refer to your reservation confirmation to verify your cancellation policy \n",
      "\n"
     ]
    }
   ],
   "source": [
    "a = 0\n",
    "for i in range(a,a+8):\n",
    "    print(df.sentence[i])\n",
    "    print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "vectorizer = CountVectorizer(analyzer='word',       \n",
    "                             min_df=3,                        # minimum reqd occurences of a word \n",
    "                             stop_words='english',             # remove stop words\n",
    "                             lowercase=True,                   # convert all words to lowercase\n",
    "                             token_pattern='[a-zA-Z0-9]{3,}',  # num chars > 3\n",
    "                             max_features=3000,             # max number of uniq words\n",
    "                            )\n",
    "\n",
    "data_vectorized = vectorizer.fit_transform(df['sentence'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LatentDirichletAllocation(batch_size=128, doc_topic_prior=None,\n",
      "                          evaluate_every=-1, learning_decay=0.7,\n",
      "                          learning_method='online', learning_offset=10.0,\n",
      "                          max_doc_update_iter=100, max_iter=10,\n",
      "                          mean_change_tol=0.001, n_components=40, n_jobs=-1,\n",
      "                          perp_tol=0.1, random_state=0, topic_word_prior=None,\n",
      "                          total_samples=1000000.0, verbose=0)\n"
     ]
    }
   ],
   "source": [
    "lda_model = LatentDirichletAllocation(n_components=40, # Number of topics\n",
    "                                      learning_method='online',\n",
    "                                      random_state=0,       \n",
    "                                      n_jobs = -1  # Use all available CPUs\n",
    "                                     )\n",
    "lda_output = lda_model.fit_transform(data_vectorized)\n",
    "\n",
    "print(lda_model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/tljh/user/lib/python3.6/site-packages/pyLDAvis/_prepare.py:257: FutureWarning: Sorting because non-concatenation axis is not aligned. A future version\n",
      "of pandas will change to not sort by default.\n",
      "\n",
      "To accept the future behavior, pass 'sort=False'.\n",
      "\n",
      "To retain the current behavior and silence the warning, pass 'sort=True'.\n",
      "\n",
      "  return pd.concat([default_term_info] + list(topic_dfs))\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<link rel=\"stylesheet\" type=\"text/css\" href=\"https://cdn.rawgit.com/bmabey/pyLDAvis/files/ldavis.v1.0.0.css\">\n",
       "\n",
       "\n",
       "<div id=\"ldavis_el13351403074147929767797251801\"></div>\n",
       "<script type=\"text/javascript\">\n",
       "\n",
       "var ldavis_el13351403074147929767797251801_data = {\"mdsDat\": {\"x\": [52.8101806640625, 61.66909408569336, 94.50421905517578, 8.152670860290527, -20.2228946685791, 130.0946807861328, 112.20576477050781, 20.300003051757812, 35.29579544067383, 33.399497985839844, -39.22332763671875, -76.31999206542969, -76.35144805908203, 104.0326919555664, 94.0611572265625, -29.72979736328125, -81.75386047363281, -115.26114654541016, 71.4150161743164, -79.80573272705078, -71.97945404052734, 64.26312255859375, -26.498144149780273, 31.73723602294922, 61.51547622680664, -49.61991882324219, 53.29402160644531, -0.3072241246700287, -48.525142669677734, -22.5277156829834, -11.22398853302002, -39.89698028564453, 36.86488723754883, 3.2649755477905273, 12.08049488067627, 0.8431587219238281, -17.604999542236328, 24.873323440551758, 2.7249741554260254, 25.646587371826172], \"y\": [107.99787902832031, -23.845094680786133, 85.49647521972656, -61.16213607788086, 60.94546890258789, 47.707427978515625, 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      "text/plain": [
       "PreparedData(topic_coordinates=                x           y  topics  cluster       Freq\n",
       "topic                                                    \n",
       "23      52.810181  107.997879       1        1  23.309673\n",
       "0       61.669094  -23.845095       2        1   7.135673\n",
       "21      94.504219   85.496475       3        1   6.933787\n",
       "22       8.152671  -61.162136       4        1   5.901442\n",
       "5      -20.222895   60.945469       5        1   5.199544\n",
       "39     130.094681   47.707428       6        1   5.174447\n",
       "37     112.205765  -46.932274       7        1   3.641742\n",
       "34      20.300003  123.798866       8        1   3.371417\n",
       "10      35.295795  -98.459053       9        1   3.215031\n",
       "24      33.399498  -40.309830      10        1   3.051413\n",
       "38     -39.223328  -32.901543      11        1   2.941073\n",
       "2      -76.319992  101.096680      12        1   2.704279\n",
       "20     -76.351448  -23.054537      13        1   2.609571\n",
       "1      104.032692   22.052193      14        1   2.491596\n",
       "3       94.061157  -11.908739      15        1   2.380405\n",
       "26     -29.729797  -61.914070      16        1   1.923049\n",
       "36     -81.753860   55.740067      17        1   1.821930\n",
       "17    -115.261147    0.317844      18        1   1.643399\n",
       "33      71.415016   33.707039      19        1   1.489288\n",
       "14     -79.805733   19.744102      20        1   1.457323\n",
       "9      -71.979454  -66.767677      21        1   1.403683\n",
       "25      64.263123  -65.771851      22        1   1.378312\n",
       "4      -26.498144  111.649246      23        1   1.286898\n",
       "32      31.737236   77.611855      24        1   0.892748\n",
       "13      61.515476   63.975536      25        1   0.817660\n",
       "28     -49.619919    5.555991      26        1   0.756039\n",
       "7       53.294022    7.669420      27        1   0.707738\n",
       "15      -0.307224   84.005600      28        1   0.542800\n",
       "12     -48.525143   71.959526      29        1   0.531173\n",
       "30     -22.527716   -7.611402      30        1   0.459936\n",
       "29     -11.223989  -90.792847      31        1   0.448935\n",
       "19     -39.896980   36.212303      32        1   0.360965\n",
       "35      36.864887   39.051250      33        1   0.301659\n",
       "6        3.264976   31.994232      34        1   0.297041\n",
       "18      12.080495   53.989876      35        1   0.273443\n",
       "27       0.843159  -24.976843      36        1   0.272854\n",
       "8      -17.605000   20.573502      37        1   0.218008\n",
       "11      24.873323   17.042814      38        1   0.218008\n",
       "31       2.724974    4.337633      39        1   0.218008\n",
       "16      25.646587   -8.449744      40        1   0.218008, topic_info=    Category        Freq      Term       Total  loglift  logprob\n",
       "763  Default  474.000000   seattle  474.000000  30.0000  30.0000\n",
       "350  Default  120.000000      free  120.000000  29.0000  29.0000\n",
       "436  Default  271.000000     hotel  271.000000  28.0000  28.0000\n",
       "744  Default   99.000000     rooms   99.000000  27.0000  27.0000\n",
       "844  Default   99.000000      stay   99.000000  26.0000  26.0000\n",
       "..       ...         ...       ...         ...      ...      ...\n",
       "323  Topic40    0.026550  favorite    6.858633   0.5742  -6.8886\n",
       "973  Topic40    0.026543   winning   10.604204   0.1381  -6.8889\n",
       "844  Topic40    0.026540      stay   99.792137  -2.1038  -6.8890\n",
       "223  Topic40    0.026537   culture    5.883395   0.7271  -6.8891\n",
       "847  Topic40    0.026537      step   10.568538   0.1413  -6.8891\n",
       "\n",
       "[2028 rows x 6 columns], token_table=      Topic      Freq       Term\n",
       "term                            \n",
       "0        15  0.940261        000\n",
       "1        18  0.621097       00pm\n",
       "2        23  0.909527        100\n",
       "3        29  0.831653       12pm\n",
       "4         5  0.277086        200\n",
       "...     ...       ...        ...\n",
       "982       4  0.246350  worldmark\n",
       "982      10  0.492700  worldmark\n",
       "983       2  0.848519      worth\n",
       "984       9  0.827556       year\n",
       "985      29  0.846565      years\n",
       "\n",
       "[1722 rows x 3 columns], R=30, lambda_step=0.01, plot_opts={'xlab': 'PC1', 'ylab': 'PC2'}, topic_order=[24, 1, 22, 23, 6, 40, 38, 35, 11, 25, 39, 3, 21, 2, 4, 27, 37, 18, 34, 15, 10, 26, 5, 33, 14, 29, 8, 16, 13, 31, 30, 20, 36, 7, 19, 28, 9, 12, 32, 17])"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pyLDAvis.enable_notebook()\n",
    "pyLDAvis.sklearn.prepare(lda_model, data_vectorized, vectorizer, mds='tsne')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Word 0</th>\n",
       "      <th>Word 1</th>\n",
       "      <th>Word 2</th>\n",
       "      <th>Word 3</th>\n",
       "      <th>Word 4</th>\n",
       "      <th>Word 5</th>\n",
       "      <th>Word 6</th>\n",
       "      <th>Word 7</th>\n",
       "      <th>Word 8</th>\n",
       "      <th>Word 9</th>\n",
       "      <th>Word 10</th>\n",
       "      <th>Word 11</th>\n",
       "      <th>Word 12</th>\n",
       "      <th>Word 13</th>\n",
       "      <th>Word 14</th>\n",
       "      <th>Word 15</th>\n",
       "      <th>Word 16</th>\n",
       "      <th>Word 17</th>\n",
       "      <th>Word 18</th>\n",
       "      <th>Word 19</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>Topic 0</td>\n",
       "      <td>seattle</td>\n",
       "      <td>hotel</td>\n",
       "      <td>inn</td>\n",
       "      <td>lake</td>\n",
       "      <td>union</td>\n",
       "      <td>stay</td>\n",
       "      <td>experience</td>\n",
       "      <td>offers</td>\n",
       "      <td>south</td>\n",
       "      <td>guests</td>\n",
       "      <td>suites</td>\n",
       "      <td>downtown</td>\n",
       "      <td>offer</td>\n",
       "      <td>modern</td>\n",
       "      <td>comfort</td>\n",
       "      <td>today</td>\n",
       "      <td>original</td>\n",
       "      <td>alfred</td>\n",
       "      <td>unique</td>\n",
       "      <td>urban</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 1</td>\n",
       "      <td>stay</td>\n",
       "      <td>make</td>\n",
       "      <td>need</td>\n",
       "      <td>sure</td>\n",
       "      <td>comfortable</td>\n",
       "      <td>time</td>\n",
       "      <td>road</td>\n",
       "      <td>extra</td>\n",
       "      <td>convenient</td>\n",
       "      <td>night</td>\n",
       "      <td>extended</td>\n",
       "      <td>enjoyable</td>\n",
       "      <td>offering</td>\n",
       "      <td>designed</td>\n",
       "      <td>hit</td>\n",
       "      <td>pride</td>\n",
       "      <td>staying</td>\n",
       "      <td>landing</td>\n",
       "      <td>soft</td>\n",
       "      <td>creature</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 2</td>\n",
       "      <td>free</td>\n",
       "      <td>wifi</td>\n",
       "      <td>guests</td>\n",
       "      <td>smoke</td>\n",
       "      <td>property</td>\n",
       "      <td>parking</td>\n",
       "      <td>proud</td>\n",
       "      <td>amenities</td>\n",
       "      <td>furnished</td>\n",
       "      <td>designed</td>\n",
       "      <td>motel</td>\n",
       "      <td>airport</td>\n",
       "      <td>stylish</td>\n",
       "      <td>hotel</td>\n",
       "      <td>lifestyle</td>\n",
       "      <td>budget</td>\n",
       "      <td>industry</td>\n",
       "      <td>providing</td>\n",
       "      <td>choice</td>\n",
       "      <td>feature</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 3</td>\n",
       "      <td>event</td>\n",
       "      <td>meeting</td>\n",
       "      <td>space</td>\n",
       "      <td>feet</td>\n",
       "      <td>square</td>\n",
       "      <td>events</td>\n",
       "      <td>meetings</td>\n",
       "      <td>000</td>\n",
       "      <td>special</td>\n",
       "      <td>planning</td>\n",
       "      <td>people</td>\n",
       "      <td>team</td>\n",
       "      <td>catering</td>\n",
       "      <td>host</td>\n",
       "      <td>spaces</td>\n",
       "      <td>matter</td>\n",
       "      <td>dedicated</td>\n",
       "      <td>grill</td>\n",
       "      <td>boardroom</td>\n",
       "      <td>private</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 4</td>\n",
       "      <td>smoking</td>\n",
       "      <td>non</td>\n",
       "      <td>100</td>\n",
       "      <td>areas</td>\n",
       "      <td>accessible</td>\n",
       "      <td>hotel</td>\n",
       "      <td>suite</td>\n",
       "      <td>reservation</td>\n",
       "      <td>tell</td>\n",
       "      <td>upgrade</td>\n",
       "      <td>public</td>\n",
       "      <td>club</td>\n",
       "      <td>attentive</td>\n",
       "      <td>cancellation</td>\n",
       "      <td>including</td>\n",
       "      <td>guests</td>\n",
       "      <td>need</td>\n",
       "      <td>rate</td>\n",
       "      <td>vary</td>\n",
       "      <td>policies</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 5</td>\n",
       "      <td>business</td>\n",
       "      <td>available</td>\n",
       "      <td>free</td>\n",
       "      <td>high</td>\n",
       "      <td>access</td>\n",
       "      <td>internet</td>\n",
       "      <td>speed</td>\n",
       "      <td>center</td>\n",
       "      <td>complimentary</td>\n",
       "      <td>parking</td>\n",
       "      <td>guest</td>\n",
       "      <td>hotel</td>\n",
       "      <td>stay</td>\n",
       "      <td>rooms</td>\n",
       "      <td>wireless</td>\n",
       "      <td>travel</td>\n",
       "      <td>room</td>\n",
       "      <td>offer</td>\n",
       "      <td>services</td>\n",
       "      <td>laundry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 6</td>\n",
       "      <td>named</td>\n",
       "      <td>gateway</td>\n",
       "      <td>grand</td>\n",
       "      <td>sheraton</td>\n",
       "      <td>provides</td>\n",
       "      <td>diverse</td>\n",
       "      <td>core</td>\n",
       "      <td>vibrant</td>\n",
       "      <td>city</td>\n",
       "      <td>pacific</td>\n",
       "      <td>located</td>\n",
       "      <td>northwest</td>\n",
       "      <td>seattle</td>\n",
       "      <td>kitchenette</td>\n",
       "      <td>basketball</td>\n",
       "      <td>bacon</td>\n",
       "      <td>small</td>\n",
       "      <td>spend</td>\n",
       "      <td>athletic</td>\n",
       "      <td>nearby</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 7</td>\n",
       "      <td>views</td>\n",
       "      <td>comforts</td>\n",
       "      <td>skyline</td>\n",
       "      <td>stunning</td>\n",
       "      <td>look</td>\n",
       "      <td>scenic</td>\n",
       "      <td>home2</td>\n",
       "      <td>diamond</td>\n",
       "      <td>technology</td>\n",
       "      <td>destinations</td>\n",
       "      <td>landmarks</td>\n",
       "      <td>enjoy</td>\n",
       "      <td>like</td>\n",
       "      <td>space</td>\n",
       "      <td>seattle</td>\n",
       "      <td>iconic</td>\n",
       "      <td>stylish</td>\n",
       "      <td>needle</td>\n",
       "      <td>settle</td>\n",
       "      <td>situated</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 8</td>\n",
       "      <td>accommodation</td>\n",
       "      <td>parking</td>\n",
       "      <td>beer</td>\n",
       "      <td>vary</td>\n",
       "      <td>mile</td>\n",
       "      <td>regency</td>\n",
       "      <td>coffee</td>\n",
       "      <td>studios</td>\n",
       "      <td>quiet</td>\n",
       "      <td>history</td>\n",
       "      <td>avenue</td>\n",
       "      <td>enjoy</td>\n",
       "      <td>2018</td>\n",
       "      <td>news</td>\n",
       "      <td>conveniently</td>\n",
       "      <td>meetings</td>\n",
       "      <td>story</td>\n",
       "      <td>accommodations</td>\n",
       "      <td>world</td>\n",
       "      <td>overlooking</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 9</td>\n",
       "      <td>queen</td>\n",
       "      <td>hill</td>\n",
       "      <td>anne</td>\n",
       "      <td>come</td>\n",
       "      <td>capitol</td>\n",
       "      <td>suite</td>\n",
       "      <td>neighborhood</td>\n",
       "      <td>door</td>\n",
       "      <td>know</td>\n",
       "      <td>just</td>\n",
       "      <td>volunteer</td>\n",
       "      <td>fireplaces</td>\n",
       "      <td>distinctive</td>\n",
       "      <td>shared</td>\n",
       "      <td>bathrooms</td>\n",
       "      <td>kimpton</td>\n",
       "      <td>shows</td>\n",
       "      <td>bacon</td>\n",
       "      <td>let</td>\n",
       "      <td>like</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 10</td>\n",
       "      <td>pool</td>\n",
       "      <td>day</td>\n",
       "      <td>outdoor</td>\n",
       "      <td>indoor</td>\n",
       "      <td>relax</td>\n",
       "      <td>heated</td>\n",
       "      <td>fitness</td>\n",
       "      <td>long</td>\n",
       "      <td>swimming</td>\n",
       "      <td>seasonal</td>\n",
       "      <td>amenities</td>\n",
       "      <td>spa</td>\n",
       "      <td>include</td>\n",
       "      <td>room</td>\n",
       "      <td>hot</td>\n",
       "      <td>stop</td>\n",
       "      <td>start</td>\n",
       "      <td>tub</td>\n",
       "      <td>fit</td>\n",
       "      <td>busy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 11</td>\n",
       "      <td>located</td>\n",
       "      <td>union</td>\n",
       "      <td>lake</td>\n",
       "      <td>downtown</td>\n",
       "      <td>seattle</td>\n",
       "      <td>leisure</td>\n",
       "      <td>reservation</td>\n",
       "      <td>perfectly</td>\n",
       "      <td>cancellation</td>\n",
       "      <td>inn</td>\n",
       "      <td>garden</td>\n",
       "      <td>hilton</td>\n",
       "      <td>hotel</td>\n",
       "      <td>business</td>\n",
       "      <td>destination</td>\n",
       "      <td>dining</td>\n",
       "      <td>city</td>\n",
       "      <td>modern</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>neighborhood</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 12</td>\n",
       "      <td>check</td>\n",
       "      <td>12pm</td>\n",
       "      <td>years</td>\n",
       "      <td>guest</td>\n",
       "      <td>rooms</td>\n",
       "      <td>smoking</td>\n",
       "      <td>floor</td>\n",
       "      <td>apartment</td>\n",
       "      <td>mason</td>\n",
       "      <td>use</td>\n",
       "      <td>500</td>\n",
       "      <td>major</td>\n",
       "      <td>time</td>\n",
       "      <td>heading</td>\n",
       "      <td>property</td>\n",
       "      <td>internet</td>\n",
       "      <td>00pm</td>\n",
       "      <td>offer</td>\n",
       "      <td>waiting</td>\n",
       "      <td>renton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 13</td>\n",
       "      <td>restaurants</td>\n",
       "      <td>shops</td>\n",
       "      <td>cultural</td>\n",
       "      <td>unique</td>\n",
       "      <td>hub</td>\n",
       "      <td>galleries</td>\n",
       "      <td>museums</td>\n",
       "      <td>boutiques</td>\n",
       "      <td>spend</td>\n",
       "      <td>sites</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>advantage</td>\n",
       "      <td>chic</td>\n",
       "      <td>activities</td>\n",
       "      <td>attractions</td>\n",
       "      <td>sophisticated</td>\n",
       "      <td>southport</td>\n",
       "      <td>caf</td>\n",
       "      <td>including</td>\n",
       "      <td>near</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 14</td>\n",
       "      <td>northwest</td>\n",
       "      <td>pacific</td>\n",
       "      <td>renovated</td>\n",
       "      <td>natural</td>\n",
       "      <td>newly</td>\n",
       "      <td>locally</td>\n",
       "      <td>inspired</td>\n",
       "      <td>urban</td>\n",
       "      <td>sourced</td>\n",
       "      <td>modern</td>\n",
       "      <td>beautifully</td>\n",
       "      <td>outdoors</td>\n",
       "      <td>menu</td>\n",
       "      <td>park</td>\n",
       "      <td>bounty</td>\n",
       "      <td>beauty</td>\n",
       "      <td>prepared</td>\n",
       "      <td>seasonal</td>\n",
       "      <td>area</td>\n",
       "      <td>culinary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 15</td>\n",
       "      <td>hotels</td>\n",
       "      <td>north</td>\n",
       "      <td>seven</td>\n",
       "      <td>guests</td>\n",
       "      <td>service</td>\n",
       "      <td>america</td>\n",
       "      <td>available</td>\n",
       "      <td>grand</td>\n",
       "      <td>sheraton</td>\n",
       "      <td>earn</td>\n",
       "      <td>book</td>\n",
       "      <td>door</td>\n",
       "      <td>range</td>\n",
       "      <td>kind</td>\n",
       "      <td>wac</td>\n",
       "      <td>notch</td>\n",
       "      <td>early</td>\n",
       "      <td>stylish</td>\n",
       "      <td>minutes</td>\n",
       "      <td>4th</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 16</td>\n",
       "      <td>bistro</td>\n",
       "      <td>wednesday</td>\n",
       "      <td>cancer</td>\n",
       "      <td>sound</td>\n",
       "      <td>cultural</td>\n",
       "      <td>table</td>\n",
       "      <td>news</td>\n",
       "      <td>laundry</td>\n",
       "      <td>couldn</td>\n",
       "      <td>beautifully</td>\n",
       "      <td>anne</td>\n",
       "      <td>staff</td>\n",
       "      <td>services</td>\n",
       "      <td>puget</td>\n",
       "      <td>furry</td>\n",
       "      <td>wine</td>\n",
       "      <td>inn</td>\n",
       "      <td>walking</td>\n",
       "      <td>meals</td>\n",
       "      <td>favorite</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 17</td>\n",
       "      <td>perfect</td>\n",
       "      <td>time</td>\n",
       "      <td>historic</td>\n",
       "      <td>hyatt</td>\n",
       "      <td>house</td>\n",
       "      <td>hospitality</td>\n",
       "      <td>mansion</td>\n",
       "      <td>trip</td>\n",
       "      <td>grand</td>\n",
       "      <td>hotel</td>\n",
       "      <td>getaway</td>\n",
       "      <td>southport</td>\n",
       "      <td>national</td>\n",
       "      <td>romantic</td>\n",
       "      <td>baillie</td>\n",
       "      <td>nichols</td>\n",
       "      <td>pensione</td>\n",
       "      <td>shafer</td>\n",
       "      <td>apartment</td>\n",
       "      <td>era</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 18</td>\n",
       "      <td>early</td>\n",
       "      <td>availability</td>\n",
       "      <td>check</td>\n",
       "      <td>worth</td>\n",
       "      <td>known</td>\n",
       "      <td>sure</td>\n",
       "      <td>train</td>\n",
       "      <td>accommodation</td>\n",
       "      <td>truly</td>\n",
       "      <td>delivers</td>\n",
       "      <td>policies</td>\n",
       "      <td>stay</td>\n",
       "      <td>soak</td>\n",
       "      <td>restaurant</td>\n",
       "      <td>dedicated</td>\n",
       "      <td>westlake</td>\n",
       "      <td>offices</td>\n",
       "      <td>incredible</td>\n",
       "      <td>sports</td>\n",
       "      <td>join</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 19</td>\n",
       "      <td>cool</td>\n",
       "      <td>touches</td>\n",
       "      <td>awesome</td>\n",
       "      <td>soon</td>\n",
       "      <td>comfortable</td>\n",
       "      <td>inside</td>\n",
       "      <td>set</td>\n",
       "      <td>step</td>\n",
       "      <td>watertown</td>\n",
       "      <td>tell</td>\n",
       "      <td>floors</td>\n",
       "      <td>haven</td>\n",
       "      <td>art</td>\n",
       "      <td>guest</td>\n",
       "      <td>rooms</td>\n",
       "      <td>like</td>\n",
       "      <td>today</td>\n",
       "      <td>kids</td>\n",
       "      <td>loft</td>\n",
       "      <td>elements</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 20</td>\n",
       "      <td>rooms</td>\n",
       "      <td>guest</td>\n",
       "      <td>options</td>\n",
       "      <td>featuring</td>\n",
       "      <td>great</td>\n",
       "      <td>comfort</td>\n",
       "      <td>variety</td>\n",
       "      <td>mind</td>\n",
       "      <td>modern</td>\n",
       "      <td>private</td>\n",
       "      <td>fresh</td>\n",
       "      <td>designed</td>\n",
       "      <td>feature</td>\n",
       "      <td>use</td>\n",
       "      <td>recently</td>\n",
       "      <td>intimate</td>\n",
       "      <td>sheraton</td>\n",
       "      <td>ironing</td>\n",
       "      <td>club</td>\n",
       "      <td>expanded</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 21</td>\n",
       "      <td>bed</td>\n",
       "      <td>suites</td>\n",
       "      <td>home</td>\n",
       "      <td>spacious</td>\n",
       "      <td>living</td>\n",
       "      <td>flat</td>\n",
       "      <td>room</td>\n",
       "      <td>beds</td>\n",
       "      <td>rooms</td>\n",
       "      <td>screen</td>\n",
       "      <td>equipped</td>\n",
       "      <td>family</td>\n",
       "      <td>studio</td>\n",
       "      <td>hotel</td>\n",
       "      <td>microwave</td>\n",
       "      <td>amenities</td>\n",
       "      <td>queen</td>\n",
       "      <td>fridge</td>\n",
       "      <td>bathroom</td>\n",
       "      <td>comfortable</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 22</td>\n",
       "      <td>space</td>\n",
       "      <td>needle</td>\n",
       "      <td>center</td>\n",
       "      <td>washington</td>\n",
       "      <td>university</td>\n",
       "      <td>seattle</td>\n",
       "      <td>pike</td>\n",
       "      <td>place</td>\n",
       "      <td>market</td>\n",
       "      <td>convention</td>\n",
       "      <td>state</td>\n",
       "      <td>away</td>\n",
       "      <td>including</td>\n",
       "      <td>attractions</td>\n",
       "      <td>medical</td>\n",
       "      <td>close</td>\n",
       "      <td>mason</td>\n",
       "      <td>hospital</td>\n",
       "      <td>campus</td>\n",
       "      <td>virginia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 23</td>\n",
       "      <td>seattle</td>\n",
       "      <td>hotel</td>\n",
       "      <td>located</td>\n",
       "      <td>downtown</td>\n",
       "      <td>airport</td>\n",
       "      <td>place</td>\n",
       "      <td>just</td>\n",
       "      <td>market</td>\n",
       "      <td>pike</td>\n",
       "      <td>away</td>\n",
       "      <td>minutes</td>\n",
       "      <td>best</td>\n",
       "      <td>near</td>\n",
       "      <td>center</td>\n",
       "      <td>inn</td>\n",
       "      <td>city</td>\n",
       "      <td>heart</td>\n",
       "      <td>waterfront</td>\n",
       "      <td>field</td>\n",
       "      <td>easy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 24</td>\n",
       "      <td>city</td>\n",
       "      <td>amenities</td>\n",
       "      <td>building</td>\n",
       "      <td>like</td>\n",
       "      <td>furnishings</td>\n",
       "      <td>seattle</td>\n",
       "      <td>emerald</td>\n",
       "      <td>enjoy</td>\n",
       "      <td>help</td>\n",
       "      <td>contemporary</td>\n",
       "      <td>view</td>\n",
       "      <td>landmark</td>\n",
       "      <td>signature</td>\n",
       "      <td>modern</td>\n",
       "      <td>floors</td>\n",
       "      <td>classic</td>\n",
       "      <td>harbor</td>\n",
       "      <td>windows</td>\n",
       "      <td>kind</td>\n",
       "      <td>things</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 25</td>\n",
       "      <td>dining</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>garden</td>\n",
       "      <td>glass</td>\n",
       "      <td>doors</td>\n",
       "      <td>world</td>\n",
       "      <td>bars</td>\n",
       "      <td>class</td>\n",
       "      <td>pay</td>\n",
       "      <td>french</td>\n",
       "      <td>fact</td>\n",
       "      <td>exciting</td>\n",
       "      <td>attention</td>\n",
       "      <td>local</td>\n",
       "      <td>experiences</td>\n",
       "      <td>favorite</td>\n",
       "      <td>staircase</td>\n",
       "      <td>known</td>\n",
       "      <td>escape</td>\n",
       "      <td>chihuly</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 26</td>\n",
       "      <td>travelers</td>\n",
       "      <td>including</td>\n",
       "      <td>amazon</td>\n",
       "      <td>business</td>\n",
       "      <td>close</td>\n",
       "      <td>town</td>\n",
       "      <td>microsoft</td>\n",
       "      <td>starbucks</td>\n",
       "      <td>businesses</td>\n",
       "      <td>boeing</td>\n",
       "      <td>headquarters</td>\n",
       "      <td>proximity</td>\n",
       "      <td>nordstrom</td>\n",
       "      <td>facebook</td>\n",
       "      <td>google</td>\n",
       "      <td>companies</td>\n",
       "      <td>500</td>\n",
       "      <td>hip</td>\n",
       "      <td>gates</td>\n",
       "      <td>shopping</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 27</td>\n",
       "      <td>societym</td>\n",
       "      <td>loft</td>\n",
       "      <td>ceilings</td>\n",
       "      <td>friends</td>\n",
       "      <td>today</td>\n",
       "      <td>elements</td>\n",
       "      <td>rooms</td>\n",
       "      <td>like</td>\n",
       "      <td>guest</td>\n",
       "      <td>floors</td>\n",
       "      <td>art</td>\n",
       "      <td>truly</td>\n",
       "      <td>conference</td>\n",
       "      <td>feature</td>\n",
       "      <td>trip</td>\n",
       "      <td>stunning</td>\n",
       "      <td>corporate</td>\n",
       "      <td>alexis</td>\n",
       "      <td>roof</td>\n",
       "      <td>long</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 28</td>\n",
       "      <td>arts</td>\n",
       "      <td>rich</td>\n",
       "      <td>spend</td>\n",
       "      <td>music</td>\n",
       "      <td>thriving</td>\n",
       "      <td>afternoon</td>\n",
       "      <td>way</td>\n",
       "      <td>period</td>\n",
       "      <td>landscape</td>\n",
       "      <td>lights</td>\n",
       "      <td>oak</td>\n",
       "      <td>area</td>\n",
       "      <td>museums</td>\n",
       "      <td>scene</td>\n",
       "      <td>interesting</td>\n",
       "      <td>haven</td>\n",
       "      <td>details</td>\n",
       "      <td>rooftop</td>\n",
       "      <td>250</td>\n",
       "      <td>hall</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 29</td>\n",
       "      <td>air</td>\n",
       "      <td>cable</td>\n",
       "      <td>balcony</td>\n",
       "      <td>conditioned</td>\n",
       "      <td>crown</td>\n",
       "      <td>conditioning</td>\n",
       "      <td>room</td>\n",
       "      <td>resort</td>\n",
       "      <td>guest</td>\n",
       "      <td>days</td>\n",
       "      <td>oasis</td>\n",
       "      <td>smoking</td>\n",
       "      <td>hospitality</td>\n",
       "      <td>500</td>\n",
       "      <td>fee</td>\n",
       "      <td>feature</td>\n",
       "      <td>garden</td>\n",
       "      <td>grand</td>\n",
       "      <td>inviting</td>\n",
       "      <td>fit</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 30</td>\n",
       "      <td>want</td>\n",
       "      <td>right</td>\n",
       "      <td>rental</td>\n",
       "      <td>breeze</td>\n",
       "      <td>destination</td>\n",
       "      <td>covered</td>\n",
       "      <td>possible</td>\n",
       "      <td>refreshing</td>\n",
       "      <td>heart</td>\n",
       "      <td>seattle</td>\n",
       "      <td>camlin</td>\n",
       "      <td>appreciate</td>\n",
       "      <td>worldmark</td>\n",
       "      <td>welcoming</td>\n",
       "      <td>steps</td>\n",
       "      <td>just</td>\n",
       "      <td>watertown</td>\n",
       "      <td>awesome</td>\n",
       "      <td>hotel</td>\n",
       "      <td>downtown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 31</td>\n",
       "      <td>bounty</td>\n",
       "      <td>tours</td>\n",
       "      <td>pacific</td>\n",
       "      <td>cities</td>\n",
       "      <td>terminals</td>\n",
       "      <td>free</td>\n",
       "      <td>cool</td>\n",
       "      <td>number</td>\n",
       "      <td>hold</td>\n",
       "      <td>resort</td>\n",
       "      <td>game</td>\n",
       "      <td>away</td>\n",
       "      <td>business</td>\n",
       "      <td>mobile</td>\n",
       "      <td>volunteer</td>\n",
       "      <td>neighborhoods</td>\n",
       "      <td>details</td>\n",
       "      <td>round</td>\n",
       "      <td>outside</td>\n",
       "      <td>look</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 32</td>\n",
       "      <td>features</td>\n",
       "      <td>cloud</td>\n",
       "      <td>silver</td>\n",
       "      <td>kitchen</td>\n",
       "      <td>broadway</td>\n",
       "      <td>rock</td>\n",
       "      <td>jimmy</td>\n",
       "      <td>hotel</td>\n",
       "      <td>late</td>\n",
       "      <td>stadium</td>\n",
       "      <td>chef</td>\n",
       "      <td>bar</td>\n",
       "      <td>casual</td>\n",
       "      <td>express</td>\n",
       "      <td>options</td>\n",
       "      <td>including</td>\n",
       "      <td>proud</td>\n",
       "      <td>success</td>\n",
       "      <td>upscale</td>\n",
       "      <td>caf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 33</td>\n",
       "      <td>neighborhood</td>\n",
       "      <td>belltown</td>\n",
       "      <td>live</td>\n",
       "      <td>music</td>\n",
       "      <td>vibrant</td>\n",
       "      <td>alike</td>\n",
       "      <td>food</td>\n",
       "      <td>neighborhoods</td>\n",
       "      <td>core</td>\n",
       "      <td>history</td>\n",
       "      <td>scene</td>\n",
       "      <td>area</td>\n",
       "      <td>waterfront</td>\n",
       "      <td>guestrooms</td>\n",
       "      <td>nestled</td>\n",
       "      <td>venues</td>\n",
       "      <td>locals</td>\n",
       "      <td>diverse</td>\n",
       "      <td>west</td>\n",
       "      <td>georgetown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 34</td>\n",
       "      <td>hotel</td>\n",
       "      <td>seattle</td>\n",
       "      <td>friendly</td>\n",
       "      <td>welcome</td>\n",
       "      <td>sound</td>\n",
       "      <td>puget</td>\n",
       "      <td>downtown</td>\n",
       "      <td>award</td>\n",
       "      <td>pet</td>\n",
       "      <td>winning</td>\n",
       "      <td>don</td>\n",
       "      <td>old</td>\n",
       "      <td>world</td>\n",
       "      <td>built</td>\n",
       "      <td>good</td>\n",
       "      <td>comfortable</td>\n",
       "      <td>style</td>\n",
       "      <td>forget</td>\n",
       "      <td>restaurant</td>\n",
       "      <td>small</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 35</td>\n",
       "      <td>outside</td>\n",
       "      <td>runs</td>\n",
       "      <td>shuttle</td>\n",
       "      <td>pride</td>\n",
       "      <td>permitted</td>\n",
       "      <td>guests</td>\n",
       "      <td>areas</td>\n",
       "      <td>designated</td>\n",
       "      <td>smoking</td>\n",
       "      <td>buildings</td>\n",
       "      <td>hotel</td>\n",
       "      <td>smoke</td>\n",
       "      <td>inviting</td>\n",
       "      <td>deep</td>\n",
       "      <td>lobby</td>\n",
       "      <td>american</td>\n",
       "      <td>spots</td>\n",
       "      <td>hit</td>\n",
       "      <td>college</td>\n",
       "      <td>work</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 36</td>\n",
       "      <td>room</td>\n",
       "      <td>views</td>\n",
       "      <td>desk</td>\n",
       "      <td>large</td>\n",
       "      <td>style</td>\n",
       "      <td>enjoy</td>\n",
       "      <td>dining</td>\n",
       "      <td>offers</td>\n",
       "      <td>comfort</td>\n",
       "      <td>level</td>\n",
       "      <td>private</td>\n",
       "      <td>gorgeous</td>\n",
       "      <td>fee</td>\n",
       "      <td>windows</td>\n",
       "      <td>vietnamese</td>\n",
       "      <td>upscale</td>\n",
       "      <td>rooftop</td>\n",
       "      <td>club</td>\n",
       "      <td>incredible</td>\n",
       "      <td>service</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 37</td>\n",
       "      <td>breakfast</td>\n",
       "      <td>hour</td>\n",
       "      <td>fitness</td>\n",
       "      <td>center</td>\n",
       "      <td>service</td>\n",
       "      <td>complimentary</td>\n",
       "      <td>enjoy</td>\n",
       "      <td>shuttle</td>\n",
       "      <td>site</td>\n",
       "      <td>morning</td>\n",
       "      <td>restaurant</td>\n",
       "      <td>convenience</td>\n",
       "      <td>facility</td>\n",
       "      <td>continental</td>\n",
       "      <td>daily</td>\n",
       "      <td>offer</td>\n",
       "      <td>hot</td>\n",
       "      <td>start</td>\n",
       "      <td>happy</td>\n",
       "      <td>bar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 38</td>\n",
       "      <td>art</td>\n",
       "      <td>museum</td>\n",
       "      <td>work</td>\n",
       "      <td>explore</td>\n",
       "      <td>area</td>\n",
       "      <td>nearby</td>\n",
       "      <td>seattle</td>\n",
       "      <td>attractions</td>\n",
       "      <td>flight</td>\n",
       "      <td>center</td>\n",
       "      <td>local</td>\n",
       "      <td>easily</td>\n",
       "      <td>state</td>\n",
       "      <td>needs</td>\n",
       "      <td>hostel</td>\n",
       "      <td>station</td>\n",
       "      <td>pike</td>\n",
       "      <td>market</td>\n",
       "      <td>catch</td>\n",
       "      <td>ready</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Topic 39</td>\n",
       "      <td>coffee</td>\n",
       "      <td>local</td>\n",
       "      <td>lobby</td>\n",
       "      <td>bar</td>\n",
       "      <td>enjoy</td>\n",
       "      <td>breakfast</td>\n",
       "      <td>experience</td>\n",
       "      <td>fresh</td>\n",
       "      <td>lounge</td>\n",
       "      <td>day</td>\n",
       "      <td>restaurant</td>\n",
       "      <td>family</td>\n",
       "      <td>friends</td>\n",
       "      <td>complimentary</td>\n",
       "      <td>hot</td>\n",
       "      <td>food</td>\n",
       "      <td>luxury</td>\n",
       "      <td>snacks</td>\n",
       "      <td>water</td>\n",
       "      <td>meet</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Word 0         Word 1     Word 2       Word 3       Word 4  \\\n",
       "Topic 0         seattle          hotel        inn         lake        union   \n",
       "Topic 1            stay           make       need         sure  comfortable   \n",
       "Topic 2            free           wifi     guests        smoke     property   \n",
       "Topic 3           event        meeting      space         feet       square   \n",
       "Topic 4         smoking            non        100        areas   accessible   \n",
       "Topic 5        business      available       free         high       access   \n",
       "Topic 6           named        gateway      grand     sheraton     provides   \n",
       "Topic 7           views       comforts    skyline     stunning         look   \n",
       "Topic 8   accommodation        parking       beer         vary         mile   \n",
       "Topic 9           queen           hill       anne         come      capitol   \n",
       "Topic 10           pool            day    outdoor       indoor        relax   \n",
       "Topic 11        located          union       lake     downtown      seattle   \n",
       "Topic 12          check           12pm      years        guest        rooms   \n",
       "Topic 13    restaurants          shops   cultural       unique          hub   \n",
       "Topic 14      northwest        pacific  renovated      natural        newly   \n",
       "Topic 15         hotels          north      seven       guests      service   \n",
       "Topic 16         bistro      wednesday     cancer        sound     cultural   \n",
       "Topic 17        perfect           time   historic        hyatt        house   \n",
       "Topic 18          early   availability      check        worth        known   \n",
       "Topic 19           cool        touches    awesome         soon  comfortable   \n",
       "Topic 20          rooms          guest    options    featuring        great   \n",
       "Topic 21            bed         suites       home     spacious       living   \n",
       "Topic 22          space         needle     center   washington   university   \n",
       "Topic 23        seattle          hotel    located     downtown      airport   \n",
       "Topic 24           city      amenities   building         like  furnishings   \n",
       "Topic 25         dining  entertainment     garden        glass        doors   \n",
       "Topic 26      travelers      including     amazon     business        close   \n",
       "Topic 27       societym           loft   ceilings      friends        today   \n",
       "Topic 28           arts           rich      spend        music     thriving   \n",
       "Topic 29            air          cable    balcony  conditioned        crown   \n",
       "Topic 30           want          right     rental       breeze  destination   \n",
       "Topic 31         bounty          tours    pacific       cities    terminals   \n",
       "Topic 32       features          cloud     silver      kitchen     broadway   \n",
       "Topic 33   neighborhood       belltown       live        music      vibrant   \n",
       "Topic 34          hotel        seattle   friendly      welcome        sound   \n",
       "Topic 35        outside           runs    shuttle        pride    permitted   \n",
       "Topic 36           room          views       desk        large        style   \n",
       "Topic 37      breakfast           hour    fitness       center      service   \n",
       "Topic 38            art         museum       work      explore         area   \n",
       "Topic 39         coffee          local      lobby          bar        enjoy   \n",
       "\n",
       "                 Word 5        Word 6         Word 7         Word 8  \\\n",
       "Topic 0            stay    experience         offers          south   \n",
       "Topic 1            time          road          extra     convenient   \n",
       "Topic 2         parking         proud      amenities      furnished   \n",
       "Topic 3          events      meetings            000        special   \n",
       "Topic 4           hotel         suite    reservation           tell   \n",
       "Topic 5        internet         speed         center  complimentary   \n",
       "Topic 6         diverse          core        vibrant           city   \n",
       "Topic 7          scenic         home2        diamond     technology   \n",
       "Topic 8         regency        coffee        studios          quiet   \n",
       "Topic 9           suite  neighborhood           door           know   \n",
       "Topic 10         heated       fitness           long       swimming   \n",
       "Topic 11        leisure   reservation      perfectly   cancellation   \n",
       "Topic 12        smoking         floor      apartment          mason   \n",
       "Topic 13      galleries       museums      boutiques          spend   \n",
       "Topic 14        locally      inspired          urban        sourced   \n",
       "Topic 15        america     available          grand       sheraton   \n",
       "Topic 16          table          news        laundry         couldn   \n",
       "Topic 17    hospitality       mansion           trip          grand   \n",
       "Topic 18           sure         train  accommodation          truly   \n",
       "Topic 19         inside           set           step      watertown   \n",
       "Topic 20        comfort       variety           mind         modern   \n",
       "Topic 21           flat          room           beds          rooms   \n",
       "Topic 22        seattle          pike          place         market   \n",
       "Topic 23          place          just         market           pike   \n",
       "Topic 24        seattle       emerald          enjoy           help   \n",
       "Topic 25          world          bars          class            pay   \n",
       "Topic 26           town     microsoft      starbucks     businesses   \n",
       "Topic 27       elements         rooms           like          guest   \n",
       "Topic 28      afternoon           way         period      landscape   \n",
       "Topic 29   conditioning          room         resort          guest   \n",
       "Topic 30        covered      possible     refreshing          heart   \n",
       "Topic 31           free          cool         number           hold   \n",
       "Topic 32           rock         jimmy          hotel           late   \n",
       "Topic 33          alike          food  neighborhoods           core   \n",
       "Topic 34          puget      downtown          award            pet   \n",
       "Topic 35         guests         areas     designated        smoking   \n",
       "Topic 36          enjoy        dining         offers        comfort   \n",
       "Topic 37  complimentary         enjoy        shuttle           site   \n",
       "Topic 38         nearby       seattle    attractions         flight   \n",
       "Topic 39      breakfast    experience          fresh         lounge   \n",
       "\n",
       "                Word 9        Word 10      Word 11      Word 12  \\\n",
       "Topic 0         guests         suites     downtown        offer   \n",
       "Topic 1          night       extended    enjoyable     offering   \n",
       "Topic 2       designed          motel      airport      stylish   \n",
       "Topic 3       planning         people         team     catering   \n",
       "Topic 4        upgrade         public         club    attentive   \n",
       "Topic 5        parking          guest        hotel         stay   \n",
       "Topic 6        pacific        located    northwest      seattle   \n",
       "Topic 7   destinations      landmarks        enjoy         like   \n",
       "Topic 8        history         avenue        enjoy         2018   \n",
       "Topic 9           just      volunteer   fireplaces  distinctive   \n",
       "Topic 10      seasonal      amenities          spa      include   \n",
       "Topic 11           inn         garden       hilton        hotel   \n",
       "Topic 12           use            500        major         time   \n",
       "Topic 13         sites  entertainment    advantage         chic   \n",
       "Topic 14        modern    beautifully     outdoors         menu   \n",
       "Topic 15          earn           book         door        range   \n",
       "Topic 16   beautifully           anne        staff     services   \n",
       "Topic 17         hotel        getaway    southport     national   \n",
       "Topic 18      delivers       policies         stay         soak   \n",
       "Topic 19          tell         floors        haven          art   \n",
       "Topic 20       private          fresh     designed      feature   \n",
       "Topic 21        screen       equipped       family       studio   \n",
       "Topic 22    convention          state         away    including   \n",
       "Topic 23          away        minutes         best         near   \n",
       "Topic 24  contemporary           view     landmark    signature   \n",
       "Topic 25        french           fact     exciting    attention   \n",
       "Topic 26        boeing   headquarters    proximity    nordstrom   \n",
       "Topic 27        floors            art        truly   conference   \n",
       "Topic 28        lights            oak         area      museums   \n",
       "Topic 29          days          oasis      smoking  hospitality   \n",
       "Topic 30       seattle         camlin   appreciate    worldmark   \n",
       "Topic 31        resort           game         away     business   \n",
       "Topic 32       stadium           chef          bar       casual   \n",
       "Topic 33       history          scene         area   waterfront   \n",
       "Topic 34       winning            don          old        world   \n",
       "Topic 35     buildings          hotel        smoke     inviting   \n",
       "Topic 36         level        private     gorgeous          fee   \n",
       "Topic 37       morning     restaurant  convenience     facility   \n",
       "Topic 38        center          local       easily        state   \n",
       "Topic 39           day     restaurant       family      friends   \n",
       "\n",
       "                Word 13       Word 14        Word 15    Word 16  \\\n",
       "Topic 0          modern       comfort          today   original   \n",
       "Topic 1        designed           hit          pride    staying   \n",
       "Topic 2           hotel     lifestyle         budget   industry   \n",
       "Topic 3            host        spaces         matter  dedicated   \n",
       "Topic 4    cancellation     including         guests       need   \n",
       "Topic 5           rooms      wireless         travel       room   \n",
       "Topic 6     kitchenette    basketball          bacon      small   \n",
       "Topic 7           space       seattle         iconic    stylish   \n",
       "Topic 8            news  conveniently       meetings      story   \n",
       "Topic 9          shared     bathrooms        kimpton      shows   \n",
       "Topic 10           room           hot           stop      start   \n",
       "Topic 11       business   destination         dining       city   \n",
       "Topic 12        heading      property       internet       00pm   \n",
       "Topic 13     activities   attractions  sophisticated  southport   \n",
       "Topic 14           park        bounty         beauty   prepared   \n",
       "Topic 15           kind           wac          notch      early   \n",
       "Topic 16          puget         furry           wine        inn   \n",
       "Topic 17       romantic       baillie        nichols   pensione   \n",
       "Topic 18     restaurant     dedicated       westlake    offices   \n",
       "Topic 19          guest         rooms           like      today   \n",
       "Topic 20            use      recently       intimate   sheraton   \n",
       "Topic 21          hotel     microwave      amenities      queen   \n",
       "Topic 22    attractions       medical          close      mason   \n",
       "Topic 23         center           inn           city      heart   \n",
       "Topic 24         modern        floors        classic     harbor   \n",
       "Topic 25          local   experiences       favorite  staircase   \n",
       "Topic 26       facebook        google      companies        500   \n",
       "Topic 27        feature          trip       stunning  corporate   \n",
       "Topic 28          scene   interesting          haven    details   \n",
       "Topic 29            500           fee        feature     garden   \n",
       "Topic 30      welcoming         steps           just  watertown   \n",
       "Topic 31         mobile     volunteer  neighborhoods    details   \n",
       "Topic 32        express       options      including      proud   \n",
       "Topic 33     guestrooms       nestled         venues     locals   \n",
       "Topic 34          built          good    comfortable      style   \n",
       "Topic 35           deep         lobby       american      spots   \n",
       "Topic 36        windows    vietnamese        upscale    rooftop   \n",
       "Topic 37    continental         daily          offer        hot   \n",
       "Topic 38          needs        hostel        station       pike   \n",
       "Topic 39  complimentary           hot           food     luxury   \n",
       "\n",
       "                 Word 17        Word 18       Word 19  \n",
       "Topic 0           alfred         unique         urban  \n",
       "Topic 1          landing           soft      creature  \n",
       "Topic 2        providing         choice       feature  \n",
       "Topic 3            grill      boardroom       private  \n",
       "Topic 4             rate           vary      policies  \n",
       "Topic 5            offer       services       laundry  \n",
       "Topic 6            spend       athletic        nearby  \n",
       "Topic 7           needle         settle      situated  \n",
       "Topic 8   accommodations          world   overlooking  \n",
       "Topic 9            bacon            let          like  \n",
       "Topic 10             tub            fit          busy  \n",
       "Topic 11          modern  entertainment  neighborhood  \n",
       "Topic 12           offer        waiting        renton  \n",
       "Topic 13             caf      including          near  \n",
       "Topic 14        seasonal           area      culinary  \n",
       "Topic 15         stylish        minutes           4th  \n",
       "Topic 16         walking          meals      favorite  \n",
       "Topic 17          shafer      apartment           era  \n",
       "Topic 18      incredible         sports          join  \n",
       "Topic 19            kids           loft      elements  \n",
       "Topic 20         ironing           club      expanded  \n",
       "Topic 21          fridge       bathroom   comfortable  \n",
       "Topic 22        hospital         campus      virginia  \n",
       "Topic 23      waterfront          field          easy  \n",
       "Topic 24         windows           kind        things  \n",
       "Topic 25           known         escape       chihuly  \n",
       "Topic 26             hip          gates      shopping  \n",
       "Topic 27          alexis           roof          long  \n",
       "Topic 28         rooftop            250          hall  \n",
       "Topic 29           grand       inviting           fit  \n",
       "Topic 30         awesome          hotel      downtown  \n",
       "Topic 31           round        outside          look  \n",
       "Topic 32         success        upscale           caf  \n",
       "Topic 33         diverse           west    georgetown  \n",
       "Topic 34          forget     restaurant         small  \n",
       "Topic 35             hit        college          work  \n",
       "Topic 36            club     incredible       service  \n",
       "Topic 37           start          happy           bar  \n",
       "Topic 38          market          catch         ready  \n",
       "Topic 39          snacks          water          meet  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show top 20 keywords for each topic\n",
    "def show_topics(vectorizer=vectorizer, lda_model=lda_model, n_words=20):\n",
    "    keywords = np.array(vectorizer.get_feature_names())\n",
    "    topic_keywords = []\n",
    "    for topic_weights in lda_model.components_:\n",
    "        top_keyword_locs = (-topic_weights).argsort()[:n_words]\n",
    "        topic_keywords.append(keywords.take(top_keyword_locs))\n",
    "    return topic_keywords\n",
    "\n",
    "topic_keywords = show_topics(vectorizer=vectorizer, lda_model=lda_model, n_words=20)        \n",
    "\n",
    "# Topic - Keywords Dataframe\n",
    "df_topic_keywords = pd.DataFrame(topic_keywords)\n",
    "df_topic_keywords.columns = ['Word '+str(i) for i in range(df_topic_keywords.shape[1])]\n",
    "df_topic_keywords.index = ['Topic '+str(i) for i in range(df_topic_keywords.shape[0])]\n",
    "df_topic_keywords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create Document - Topic Matrix\n",
    "lda_output = lda_model.transform(data_vectorized)\n",
    "\n",
    "# column names\n",
    "topicnames = [\"Topic\" + str(i) for i in range(40)]\n",
    "\n",
    "# index names\n",
    "docnames = [\"Doc\" + str(i) for i in range(len(data))]\n",
    "\n",
    "# Make the pandas dataframe\n",
    "df_document_topic = pd.DataFrame(np.round(lda_output, 2), columns=topicnames, index=docnames)\n",
    "\n",
    "# Get dominant topic for each document\n",
    "dominant_topic = np.argmax(df_document_topic.values, axis=1)\n",
    "df_document_topic['dominant_topic'] = dominant_topic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
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       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Doc7</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Doc8</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Doc9</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Topic0  Topic1  Topic2  Topic3  Topic4  Topic5  Topic6  Topic7  Topic8  \\\n",
       "Doc0    0.47    0.00    0.00    0.00    0.00    0.00    0.00    0.00    0.00   \n",
       "Doc1    0.00    0.00    0.00    0.00    0.75    0.00    0.00    0.00    0.00   \n",
       "Doc2    0.00    0.00    0.00    0.00    0.43    0.00    0.00    0.00    0.00   \n",
       "Doc3    0.00    0.00    0.00    0.00    0.34    0.00    0.00    0.00    0.00   \n",
       "Doc4    0.01    0.01    0.01    0.01    0.01    0.01    0.01    0.01    0.01   \n",
       "Doc5    0.01    0.01    0.01    0.01    0.01    0.01    0.01    0.01    0.01   \n",
       "Doc6    0.00    0.00    0.00    0.00    0.84    0.00    0.00    0.00    0.00   \n",
       "Doc7    0.01    0.01    0.01    0.01    0.67    0.01    0.01    0.01    0.01   \n",
       "Doc8    0.00    0.00    0.00    0.00    0.00    0.00    0.30    0.00    0.00   \n",
       "Doc9    0.00    0.00    0.00    0.00    0.00    0.00    0.00    0.00    0.00   \n",
       "\n",
       "      Topic9  Topic10  Topic11  Topic12  Topic13  Topic14  Topic15  Topic16  \\\n",
       "Doc0    0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "Doc1    0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "Doc2    0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "Doc3    0.00     0.17     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "Doc4    0.01     0.01     0.01     0.51     0.01     0.01     0.01     0.01   \n",
       "Doc5    0.01     0.01     0.01     0.51     0.01     0.01     0.01     0.01   \n",
       "Doc6    0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "Doc7    0.01     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "Doc8    0.00     0.00     0.00     0.00     0.00     0.17     0.00     0.00   \n",
       "Doc9    0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "\n",
       "      Topic17  Topic18  Topic19  Topic20  Topic21  Topic22  Topic23  Topic24  \\\n",
       "Doc0     0.00     0.00     0.00     0.00     0.00     0.00     0.39     0.00   \n",
       "Doc1     0.00     0.00     0.00     0.17     0.00     0.00     0.00     0.00   \n",
       "Doc2     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "Doc3     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "Doc4     0.01     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "Doc5     0.01     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "Doc6     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "Doc7     0.01     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "Doc8     0.00     0.00     0.00     0.00     0.00     0.00     0.25     0.00   \n",
       "Doc9     0.00     0.00     0.00     0.00     0.00     0.32     0.06     0.00   \n",
       "\n",
       "      Topic25  Topic26  Topic27  Topic28  Topic29  Topic30  Topic31  Topic32  \\\n",
       "Doc0     0.07     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "Doc1     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "Doc2     0.00     0.00     0.00     0.15     0.00     0.00     0.00     0.00   \n",
       "Doc3     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "Doc4     0.01     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "Doc5     0.01     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "Doc6     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "Doc7     0.01     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "Doc8     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "Doc9     0.58     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "\n",
       "      Topic33  Topic34  Topic35  Topic36  Topic37  Topic38  Topic39  \\\n",
       "Doc0     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "Doc1     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "Doc2     0.00     0.00     0.00     0.29     0.00     0.00     0.00   \n",
       "Doc3     0.00     0.00     0.00     0.34     0.00     0.00     0.00   \n",
       "Doc4     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "Doc5     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "Doc6     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "Doc7     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "Doc8     0.22     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "Doc9     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "\n",
       "      dominant_topic  \n",
       "Doc0               0  \n",
       "Doc1               4  \n",
       "Doc2               4  \n",
       "Doc3               4  \n",
       "Doc4              12  \n",
       "Doc5              12  \n",
       "Doc6               4  \n",
       "Doc7               4  \n",
       "Doc8               6  \n",
       "Doc9              25  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_document_topic.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_document_topic.reset_index(inplace=True)\n",
    "df_sent_topic= pd.merge(df, df_document_topic, left_index=True, right_index=True)\n",
    "df_sent_topic.drop('index', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sentence</th>\n",
       "      <th>name</th>\n",
       "      <th>Topic0</th>\n",
       "      <th>Topic1</th>\n",
       "      <th>Topic2</th>\n",
       "      <th>Topic3</th>\n",
       "      <th>Topic4</th>\n",
       "      <th>Topic5</th>\n",
       "      <th>Topic6</th>\n",
       "      <th>Topic7</th>\n",
       "      <th>Topic8</th>\n",
       "      <th>Topic9</th>\n",
       "      <th>Topic10</th>\n",
       "      <th>Topic11</th>\n",
       "      <th>Topic12</th>\n",
       "      <th>Topic13</th>\n",
       "      <th>Topic14</th>\n",
       "      <th>Topic15</th>\n",
       "      <th>Topic16</th>\n",
       "      <th>Topic17</th>\n",
       "      <th>Topic18</th>\n",
       "      <th>Topic19</th>\n",
       "      <th>Topic20</th>\n",
       "      <th>Topic21</th>\n",
       "      <th>Topic22</th>\n",
       "      <th>Topic23</th>\n",
       "      <th>Topic24</th>\n",
       "      <th>Topic25</th>\n",
       "      <th>Topic26</th>\n",
       "      <th>Topic27</th>\n",
       "      <th>Topic28</th>\n",
       "      <th>Topic29</th>\n",
       "      <th>Topic30</th>\n",
       "      <th>Topic31</th>\n",
       "      <th>Topic32</th>\n",
       "      <th>Topic33</th>\n",
       "      <th>Topic34</th>\n",
       "      <th>Topic35</th>\n",
       "      <th>Topic36</th>\n",
       "      <th>Topic37</th>\n",
       "      <th>Topic38</th>\n",
       "      <th>Topic39</th>\n",
       "      <th>dominant_topic</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Located on the southern tip of Lake Union the ...</td>\n",
       "      <td>Hilton Garden Inn Seattle Downtown</td>\n",
       "      <td>0.47</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.07</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Non Smoking Hotel is 100 non smoking including...</td>\n",
       "      <td>Hilton Garden Inn Seattle Downtown</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>A fee of up to 250 USD will be assessed for sm...</td>\n",
       "      <td>Hilton Garden Inn Seattle Downtown</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Please ask the Front Desk for locations of des...</td>\n",
       "      <td>Hilton Garden Inn Seattle Downtown</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Check in 4 00 pm</td>\n",
       "      <td>Hilton Garden Inn Seattle Downtown</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Check out 12 00 pm</td>\n",
       "      <td>Hilton Garden Inn Seattle Downtown</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Cancellation policies may vary depending on th...</td>\n",
       "      <td>Hilton Garden Inn Seattle Downtown</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.84</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Please refer to your reservation confirmation ...</td>\n",
       "      <td>Hilton Garden Inn Seattle Downtown</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Located in the city s vibrant core the Sherato...</td>\n",
       "      <td>Sheraton Grand Seattle</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Step out of our front doors to find gourmet di...</td>\n",
       "      <td>Sheraton Grand Seattle</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            sentence  \\\n",
       "0  Located on the southern tip of Lake Union the ...   \n",
       "1  Non Smoking Hotel is 100 non smoking including...   \n",
       "2  A fee of up to 250 USD will be assessed for sm...   \n",
       "3  Please ask the Front Desk for locations of des...   \n",
       "4                                   Check in 4 00 pm   \n",
       "5                                 Check out 12 00 pm   \n",
       "6  Cancellation policies may vary depending on th...   \n",
       "7  Please refer to your reservation confirmation ...   \n",
       "8  Located in the city s vibrant core the Sherato...   \n",
       "9  Step out of our front doors to find gourmet di...   \n",
       "\n",
       "                                 name  Topic0  Topic1  Topic2  Topic3  Topic4  \\\n",
       "0  Hilton Garden Inn Seattle Downtown    0.47    0.00    0.00    0.00    0.00   \n",
       "1  Hilton Garden Inn Seattle Downtown    0.00    0.00    0.00    0.00    0.75   \n",
       "2  Hilton Garden Inn Seattle Downtown    0.00    0.00    0.00    0.00    0.43   \n",
       "3  Hilton Garden Inn Seattle Downtown    0.00    0.00    0.00    0.00    0.34   \n",
       "4  Hilton Garden Inn Seattle Downtown    0.01    0.01    0.01    0.01    0.01   \n",
       "5  Hilton Garden Inn Seattle Downtown    0.01    0.01    0.01    0.01    0.01   \n",
       "6  Hilton Garden Inn Seattle Downtown    0.00    0.00    0.00    0.00    0.84   \n",
       "7  Hilton Garden Inn Seattle Downtown    0.01    0.01    0.01    0.01    0.67   \n",
       "8              Sheraton Grand Seattle    0.00    0.00    0.00    0.00    0.00   \n",
       "9              Sheraton Grand Seattle    0.00    0.00    0.00    0.00    0.00   \n",
       "\n",
       "   Topic5  Topic6  Topic7  Topic8  Topic9  Topic10  Topic11  Topic12  Topic13  \\\n",
       "0    0.00    0.00    0.00    0.00    0.00     0.00     0.00     0.00     0.00   \n",
       "1    0.00    0.00    0.00    0.00    0.00     0.00     0.00     0.00     0.00   \n",
       "2    0.00    0.00    0.00    0.00    0.00     0.00     0.00     0.00     0.00   \n",
       "3    0.00    0.00    0.00    0.00    0.00     0.17     0.00     0.00     0.00   \n",
       "4    0.01    0.01    0.01    0.01    0.01     0.01     0.01     0.51     0.01   \n",
       "5    0.01    0.01    0.01    0.01    0.01     0.01     0.01     0.51     0.01   \n",
       "6    0.00    0.00    0.00    0.00    0.00     0.00     0.00     0.00     0.00   \n",
       "7    0.01    0.01    0.01    0.01    0.01     0.01     0.01     0.01     0.01   \n",
       "8    0.00    0.30    0.00    0.00    0.00     0.00     0.00     0.00     0.00   \n",
       "9    0.00    0.00    0.00    0.00    0.00     0.00     0.00     0.00     0.00   \n",
       "\n",
       "   Topic14  Topic15  Topic16  Topic17  Topic18  Topic19  Topic20  Topic21  \\\n",
       "0     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "1     0.00     0.00     0.00     0.00     0.00     0.00     0.17     0.00   \n",
       "2     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "3     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "4     0.01     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "5     0.01     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "6     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "7     0.01     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "8     0.17     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "9     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "\n",
       "   Topic22  Topic23  Topic24  Topic25  Topic26  Topic27  Topic28  Topic29  \\\n",
       "0     0.00     0.39     0.00     0.07     0.00     0.00     0.00     0.00   \n",
       "1     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "2     0.00     0.00     0.00     0.00     0.00     0.00     0.15     0.00   \n",
       "3     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "4     0.01     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "5     0.01     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "6     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "7     0.01     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "8     0.00     0.25     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "9     0.32     0.06     0.00     0.58     0.00     0.00     0.00     0.00   \n",
       "\n",
       "   Topic30  Topic31  Topic32  Topic33  Topic34  Topic35  Topic36  Topic37  \\\n",
       "0     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "1     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "2     0.00     0.00     0.00     0.00     0.00     0.00     0.29     0.00   \n",
       "3     0.00     0.00     0.00     0.00     0.00     0.00     0.34     0.00   \n",
       "4     0.01     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "5     0.01     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "6     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "7     0.01     0.01     0.01     0.01     0.01     0.01     0.01     0.01   \n",
       "8     0.00     0.00     0.00     0.22     0.00     0.00     0.00     0.00   \n",
       "9     0.00     0.00     0.00     0.00     0.00     0.00     0.00     0.00   \n",
       "\n",
       "   Topic38  Topic39  dominant_topic  \n",
       "0     0.00     0.00               0  \n",
       "1     0.00     0.00               4  \n",
       "2     0.00     0.00               4  \n",
       "3     0.00     0.00               4  \n",
       "4     0.01     0.01              12  \n",
       "5     0.01     0.01              12  \n",
       "6     0.00     0.00               4  \n",
       "7     0.01     0.01               4  \n",
       "8     0.00     0.00               6  \n",
       "9     0.00     0.00              25  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sent_topic.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>sentence</th>\n",
       "      <th>dominant_topic</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Located on the southern tip of Lake Union the ...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Non Smoking Hotel is 100 non smoking including...</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>A fee of up to 250 USD will be assessed for sm...</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Please ask the Front Desk for locations of des...</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Check in 4 00 pm</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Check out 12 00 pm</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Cancellation policies may vary depending on th...</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Please refer to your reservation confirmation ...</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            sentence  dominant_topic\n",
       "0  Located on the southern tip of Lake Union the ...               0\n",
       "1  Non Smoking Hotel is 100 non smoking including...               4\n",
       "2  A fee of up to 250 USD will be assessed for sm...               4\n",
       "3  Please ask the Front Desk for locations of des...               4\n",
       "4                                   Check in 4 00 pm              12\n",
       "5                                 Check out 12 00 pm              12\n",
       "6  Cancellation policies may vary depending on th...               4\n",
       "7  Please refer to your reservation confirmation ...               4"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sent_topic.loc[df_sent_topic['name'] == 'Hilton Garden Inn Seattle Downtown'][['sentence', 'dominant_topic']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>1053</td>\n",
       "      <td>The Spa at the WAC will spoil you with a compl...</td>\n",
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       "      <td>605</td>\n",
       "      <td>Non Smoking Hotel</td>\n",
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       "      <td>69</td>\n",
       "      <td>A fee of up to 250 USD will be assessed for sm...</td>\n",
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       "      <td>Non Smoking Hotel is 100 non smoking including...</td>\n",
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       "      <td>737</td>\n",
       "      <td>The accommodations are romantic and timeless a...</td>\n",
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       "      <td>263</td>\n",
       "      <td>Upgrade to a Premium Suite to enjoy compliment...</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>479</td>\n",
       "      <td>Our SeaTac hotel is a non smoking facility</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Non Smoking Hotel is 100 non smoking including...</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               sentence  dominant_topic\n",
       "1053  The Spa at the WAC will spoil you with a compl...               4\n",
       "697                 Our hotel is completely non smoking               4\n",
       "70    Please ask the Front Desk for locations of des...               4\n",
       "7     Please refer to your reservation confirmation ...               4\n",
       "23    We do not allow smoking in our rooms public ar...               4\n",
       "1144                                    100 non smoking               4\n",
       "605                                  Non Smoking Hotel                4\n",
       "69    A fee of up to 250 USD will be assessed for sm...               4\n",
       "102   The characters Attentive staff members who alw...               4\n",
       "431   100 non smoking and accessible accommodations ...               4\n",
       "6     Cancellation policies may vary depending on th...               4\n",
       "68    Non Smoking Hotel is 100 non smoking including...               4\n",
       "737   The accommodations are romantic and timeless a...               4\n",
       "3     Please ask the Front Desk for locations of des...               4\n",
       "1147  Cancellation policies may vary depending on th...               4\n",
       "2     A fee of up to 250 USD will be assessed for sm...               4\n",
       "81                       All guestrooms are non smoking               4\n",
       "263   Upgrade to a Premium Suite to enjoy compliment...               4\n",
       "479         Our SeaTac hotel is a non smoking facility                4\n",
       "1     Non Smoking Hotel is 100 non smoking including...               4"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sent_topic.loc[df_sent_topic['dominant_topic'] == 4][['sentence', 'dominant_topic']].sample(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <td>Check in begins at 4 00pm</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>546</td>\n",
       "      <td>Check emails in the Work Zone</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>82</td>\n",
       "      <td>Late check out is subject to availability</td>\n",
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       "      <td>4</td>\n",
       "      <td>Check in 4 00 pm</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Check out 12 00 pm</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>71</td>\n",
       "      <td>Check in 4 00 pm Check out 12 00 pm</td>\n",
       "      <td>12</td>\n",
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      ],
      "text/plain": [
       "                                         sentence  dominant_topic\n",
       "604                Check in 15 00 check out 11 00              12\n",
       "24    Check in is at 3pm and check out is at 12pm              12\n",
       "608                Check in 15 00 check out 11 00              12\n",
       "78                      Check in begins at 4 00pm              12\n",
       "546                Check emails in the Work Zone               12\n",
       "82     Late check out is subject to availability               12\n",
       "1146                           Check out 12 00 pm              12\n",
       "4                                Check in 4 00 pm              12\n",
       "5                              Check out 12 00 pm              12\n",
       "71           Check in 4 00 pm Check out 12 00 pm               12"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sent_topic.loc[df_sent_topic['dominant_topic'] == 12][['sentence', 'dominant_topic']].sample(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 20 sentences that belong to topic 4 and we will remove\n",
      "There are 19 sentences that belong to topic 12 and we will remove\n"
     ]
    }
   ],
   "source": [
    "print('There are', len(df_sent_topic.loc[df_sent_topic['dominant_topic'] == 4]), 'sentences that belong to topic 4 and we will remove')\n",
    "print('There are', len(df_sent_topic.loc[df_sent_topic['dominant_topic'] == 12]), 'sentences that belong to topic 12 and we will remove')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>17</td>\n",
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       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>33</td>\n",
       "      <td>15</td>\n",
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       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>26</td>\n",
       "      <td>14</td>\n",
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       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>9</td>\n",
       "      <td>14</td>\n",
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       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>14</td>\n",
       "      <td>11</td>\n",
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       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>25</td>\n",
       "      <td>7</td>\n",
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       "      <td>24</td>\n",
       "      <td>13</td>\n",
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       "      <td>6</td>\n",
       "      <td>2</td>\n",
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       "      <td>31</td>\n",
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       "      <td>1</td>\n",
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       "      <td>32</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
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       "      <td>33</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
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       "      <td>34</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
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       "      <td>35</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
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      ],
      "text/plain": [
       "    Topic #  Num Sentences\n",
       "0        23            302\n",
       "1         0            129\n",
       "2        21             87\n",
       "3         5             72\n",
       "4        39             68\n",
       "5        22             56\n",
       "6        37             46\n",
       "7        10             44\n",
       "8        34             40\n",
       "9        24             37\n",
       "10        3             37\n",
       "11        2             32\n",
       "12        1             31\n",
       "13       20             28\n",
       "14       38             26\n",
       "15       36             21\n",
       "16        4             20\n",
       "17       12             19\n",
       "18       17             17\n",
       "19       33             15\n",
       "20       26             14\n",
       "21        9             14\n",
       "22       14             11\n",
       "23       25              7\n",
       "24       13              6\n",
       "25       28              6\n",
       "26       32              5\n",
       "27       29              4\n",
       "28       30              4\n",
       "29        7              3\n",
       "30        6              2\n",
       "31       35              1\n",
       "32       27              1\n",
       "33       15              1\n",
       "34       19              1\n",
       "35       18              1"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_topic_distribution = df_document_topic['dominant_topic'].value_counts().reset_index(name=\"Num Sentences\")\n",
    "df_topic_distribution.columns = ['Topic #', 'Num Sentences']\n",
    "df_topic_distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_sent_topic_clean = df_sent_topic.drop(df_sent_topic[(df_sent_topic.dominant_topic == 4) | (df_sent_topic.dominant_topic == 12)].index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_description = df_sent_topic_clean[['sentence','name']]\n",
    "df_description = df_description.groupby('name')['sentence'].agg(lambda col: ' '.join(col)).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>sentence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>11th Avenue Inn Bed and Breakfast</td>\n",
       "      <td>Walk to the Pike Place Market and to the other...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Ace Hotel Seattle</td>\n",
       "      <td>We fell in love with a former maritime workers...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Aloft Seattle Redmond</td>\n",
       "      <td>Celebrate your style at Aloft Seattle Redmond ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Americas Best Value Inn Shoreline / Seattle North</td>\n",
       "      <td>Americas Best Value Inn Shoreline Seattle Nort...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Ballard Inn</td>\n",
       "      <td>Historic Style with Modern Amenities The Balla...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                name  \\\n",
       "0                  11th Avenue Inn Bed and Breakfast   \n",
       "1                                  Ace Hotel Seattle   \n",
       "2                              Aloft Seattle Redmond   \n",
       "3  Americas Best Value Inn Shoreline / Seattle North   \n",
       "4                                        Ballard Inn   \n",
       "\n",
       "                                            sentence  \n",
       "0  Walk to the Pike Place Market and to the other...  \n",
       "1  We fell in love with a former maritime workers...  \n",
       "2  Celebrate your style at Aloft Seattle Redmond ...  \n",
       "3  Americas Best Value Inn Shoreline Seattle Nort...  \n",
       "4  Historic Style with Modern Amenities The Balla...  "
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_description.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Located on the southern tip of Lake Union the Hilton Garden Inn Seattle Downtown hotel is perfectly located for business and leisure'"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_description['sentence'][45]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_description.set_index('name', inplace = True)\n",
    "tf = TfidfVectorizer(analyzer='word', ngram_range=(1, 3), min_df=0, stop_words='english')\n",
    "tfidf_matrix = tf.fit_transform(df_description['sentence'])\n",
    "cosine_similarities = linear_kernel(tfidf_matrix, tfidf_matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "indices = pd.Series(df_description.index)\n",
    "def recommendations(name, cosine_similarities = cosine_similarities):\n",
    "    \n",
    "    recommended_hotels = []\n",
    "    \n",
    "    # gettin the index of the hotel that matches the name\n",
    "    idx = indices[indices == name].index[0]\n",
    "\n",
    "    # creating a Series with the similarity scores in descending order\n",
    "    score_series = pd.Series(cosine_similarities[idx]).sort_values(ascending = False)\n",
    "\n",
    "    # getting the indexes of the 5 most similar hotels except itself\n",
    "    top_10_indexes = list(score_series.iloc[1:6].index)\n",
    "    \n",
    "    # populating the list with the names of the top 5 matching hotels\n",
    "    for i in top_10_indexes:\n",
    "        recommended_hotels.append(list(df_description.index)[i])\n",
    "        \n",
    "    return recommended_hotels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Silver Cloud Inn - Seattle Lake Union',\n",
       " 'Residence Inn by Marriott Seattle Downtown/Lake Union',\n",
       " 'Staybridge Suites Seattle Downtown - Lake Union',\n",
       " 'Homewood Suites by Hilton Seattle Downtown',\n",
       " 'Days Inn by Wyndham Seattle North of Downtown']"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recommendations('Hilton Garden Inn Seattle Downtown')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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